About the event

Real-time stream processing is growing exponentially in recent years, businesses need to gather insights from real-time data as soon as it’s generated. To do this, developers and software architects use various pipelines and tools to capture and process data in motion. Real-time stream processing has its own challenges such as windowing, event time and late events, streaming fault tolerance, and processing guarantees. On the other hand, Spring is all about simplicity, and the question becomes how can you develop a real-time stream processing in Spring?

In this talk, you will learn how to overcome these challenges and best practices for real-time stream processing using the Hazelcast open-source platform. The talk will include a demo to show how you can optimize your real-time streaming projects in Spring in the following areas: scalability, performance, failover, reliability, and data recovery, the code will be available on Github.

Speaker Bio

Fawaz is a Developer Advocate at Hazelcast, with 20+ years of experience in software development, machine learning, and real-time intelligent applications. He holds a Ph.D. in Computer Science and has worked in the private sector as well as academia as a researcher and senior lecturer. He has published over 46 scientific papers in the fields of machine learning and data science. His strengths and skills lie within the fields of real-time applications, IoT & Edge, distributed systems, and cloud technologies.

This event is organised by RecWorks on behalf of the London Java Community.

The London Java Community is sponsored by JFrog, Sonatype and Snyk

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